InnerGroup - AI adoption: Progress or pilot mode? What your data tells us

On InnerGroup #MondayQuestion, I asked, “Has the adoption of AI been as deep as you anticipated at the start of the year? Where does your team stand today?”

Why did I ask this? There’s plenty of hype out there, but I was looking for real, grounded insights from marketing and creative leaders on the front line.

The scores are on the doors. Here’s what you told us:

• Integrated AI in core workflow 50%
• Testing AI tools but not live 6%
• Using AI ad-hoc 38%
• AI access is limited by policy 6%

So, what does this mean for in-house teams navigating the AI curve?

Start with a business problem, not the tech

Before chasing AI tools, define your objective. What problem are you trying to solve? What’s the benefit to your team or organization? With 88% of teams already using AI either ad hoc or in core workflows, it’s important to ensure each implementation is tied to a real business need.

Begin small, but begin

You don’t need to overhaul everything at once. As the saying by Laozi (Lao Tzu), the ancient Chinese philosopher, goes, “A journey of a thousand miles begins with a single step.” Focus on a use case that’s simple, measurable, and useful. It might be adapting or localizing assets for a particular media or channel, automating a repetitive task, or whatever creates momentum. This incremental approach mirrors how most teams are engaging AI today. 94% are already beyond initial testing, using AI either in isolated cases or fully integrated into workflows.

As marketing expert Guy Kawasaki, known for helping popularise Apple’s Macintosh computer, once said, “The hardest thing about getting started is getting started.” The quote speaks to the psychological barriers that often hold us back from taking that critical first step toward a goal. For the 8% of you who are testing AI tools but not yet live, remember: progress over perfection. Exploration is still in momentum. What matters most is that you’ve started. The rest? Well, it builds from there.

Set KPIs and show your work

Once you’ve chosen a use case, define success. Set KPIs and build a lightweight governance framework to track progress. You might not need to report these formally, but demoing your progress (even informally) keeps your team accountable. It’s like training for a triathlon: progress accelerates when someone’s watching.

Given that only 6% of teams are still in the testing phase, this is a key moment for teams to define success metrics and evolve from experimentation into measurable outcomes.

Don’t chase every new tool

If you hit your KPIs, great. If not, your framework still helps you course-correct. It keeps you from falling into the trap of jumping to the next flashy AI solution without results. Consistency and clarity beat sporadic experimentation every time.

With 38% of teams using AI ad hoc, this is a common pitfall. Building structure and discipline around tool usage is a necessary next step.

Agile innovation is the long game

AI adoption is a series of sprints towards continuously clearing your backlog. My favourite mantra here is: “Inch by inch, life’s a cinch. Yard by yard, it’s hard.” Applied to innovation, it’s a reminder that small, focused wins lead to real transformation.

Nearly half of the teams have already integrated AI into their core workflows. This shows that sustained, intentional effort is already delivering real progress.

Final thought…

If your team is somewhere between testing and tactically using AI, you’re not alone. That’s exactly where many in-house marketing teams are sitting right now. The key is to keep learning, keep measuring, and keep moving forward, one smart step at a time.

If you want to share how your team is tackling AI or where you’re hitting blockers, I’d love to hear from you.

Please follow InnerGroup on LinkedIn for ongoing insights from leading in-house teams. You can also visit innergroup.com to explore how in-house marketing models are evolving and how we're supporting that shift.